DECOVID

  • Funded by UK Research and Innovation (UKRI)
  • Total publications:0 publications

Grant number: ATI-1

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Key facts

  • Disease

    COVID-19
  • Funder

    UK Research and Innovation (UKRI)
  • Principal Investigator

    Pending
  • Research Location

    United Kingdom
  • Lead Research Institution

    Alan Turing Institute
  • Research Priority Alignment

    N/A
  • Research Category

    Clinical characterisation and management

  • Research Subcategory

    Prognostic factors for disease severity

  • Special Interest Tags

    Data Management and Data Sharing

  • Study Subject

    Other

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Unspecified

  • Vulnerable Population

    Unspecified

  • Occupations of Interest

    Unspecified

Abstract

DECOVID aims to address urgent questions that are actionable to frontline clinical and operational staff at a local (NHS hospital) level to support better care and management in the time scale of the COVID-19 pandemic; from being reactive to predictive; to inform what best practice could be, and then share this as rapidly as possible across the NHS and beyond. Our approach is to establish a unique granular, acute care medical database during the COVID-19 crisis, by targeting digitally mature hospital trusts (those with electronic health records) and incrementally collecting all acute care activity across all NHS Trusts to support high quality data capture from the start to the end of the current pandemic. These data will in turn be linked into existing national datasets, such as from primary care, in order to allow for greater understanding into the pre-morbid states of patients with the coronavirus, and therefore the window of intervention.